The primary event in the tactile recognition of object of different shapes pressed onto, vibrate or stoked across the skin surface is the transduction of the mechanical signal into trains of nerve impulses by the mechanoreceptors. Although we can record the response of single mechanoreceptor afferents, the stresses and deformations beneath the skin surface as well as the "relevant stimulus" (expressed as a particular combination of stress and strain components in the neighborhood of a receptor) to which each class of cutaneous mechanoreceptors responds are unknown at present. It is the purpose of this proposal to apply computational methods to perform mechanical analyses of reliable models that closely approximate the primate fingertip so that the relevant stimuli to the mechanoreceptors can be determined and verifiable quantitative predictions can be made about the peripheral neural response to prescribed stimuli applied to the fingertip. 1) Typical undistorted geometries of the monkey and human fingertips, their subcutaneous structure and constitutive equations will be established using data from our previous experiments and published literature. A variety of mechanistic models of the fingertip increasing in complexity and approaching the actual fingertip will be developed; 2) Available finite element method computer codes will be used with suitable modifications for a mechanical analysis of the fingertip models under prescribed stimuli. The predicted deformation behavior of the skin surface and subcutaneous tissues will be checked with data from previously obtained photographic and video images; 3) Models of transduction for each receptor type will be hypothesized by matching the spatial and temporal profiles of calculated stresses and strains at typical receptor locations with the profiles of neural responses available from selected earlier experiments performed in our laboratory; 4) Models of the fingertip and the receptor will be validated by using them to predict the known receptor response under stepping and stroking of stimuli used in our earlier experiments; 5) The models will be used to predict the results of planned neurophysiological experiments.